Iris classifier

This project trains and evaluates a machine learning model using Decision Tree Classifier on the classic Iris dataset.

• Jupyter Notebook contains experiments, exploration, and testing of different models, located in notebook folder.
• The Python scripts focus on the final model using the Decision Tree classifier, located in src folder.
• The confusion matrix plot and the saved model stored in the outputs folder.

project structure

• ├── notebooks/
• • iris_model.ipynb # Jupyter notebook (experiments, exploration)
• ├── src/
• • train.py # Train model, save confusion matrix + model file
• • test.py # Load model and evaluate on test set
• ├── outputs/
• • confusion_matrix.png # Confusion matrix plot
• • decision_tree_model.pkl# Saved model
• ├── requirements.txt # Python dependencies
• └── README.md # Project documentation

setup instructions

• download the folder
• create environment: run : ```bash py -m venv venv

Linux/macOS: source venv/bin/activate Windows: venv\Scripts\activate

Install dependencies by running:

pip install -r requirements.txt

train the model by running in terminal:

py src/train.py

test the model by running in terminal:

py src/test.py